PomaOddsRatio: Logistic Regression Model Odds Ratios

In POMA: User-friendly Workflow for Pre-processing and Statistical Analysis of Mass Spectrometry Data

Description

PomaOddsRatio() calculates the Odds Ratios for each feature from a logistic regression model using the binary outcome (group/type must be a binary factor) as a dependent variable.

Usage

PomaOddsRatio(data, feature_name = NULL, covariates = FALSE, showCI = TRUE)

Arguments

data	A MSnSet object. First pData column must be the subject group/type.
feature_name	A vector with the name/s of feature/s that will be used to fit the model. If it's NULL (default), all variables will be included in the model.
covariates	Logical that indicates if covariates will be included in logistic regression model. Default is FALSE.
showCI	Logical that indicates if the 95% confidence intervals will be plotted. Default is TRUE.

Value

A data frame with the Odds Ratios for all features with their 95% confidence intervals and a ggplot2 object.

Author(s)

Pol Castellano-Escuder

Examples

data("st000336")

st000336 %>% 
  PomaImpute() %>%
  PomaNorm() %>%
  PomaOddsRatio(feature_name = c("glutamic_acid", "glutamine", 
                                 "glycine", "histidine"))

POMA documentation built on Nov. 8, 2020, 6:26 p.m.